The current state of drug discovery techniques largely focus on searching for a single drug which will effectively treat a disease. In the past, such techniques have been successful for diseases which are “locked in” to a single pathway for survival and/or regeneration within its host. For example, penicillin was discovered to be successful in treating many forms of bacterial diseases. However, for more complex diseases, such as the various cancers; viral diseases, such as HIV (AIDS), SARS, and others; and drug-resistant bacteria, such as tuberculosis and others, single drug treatments have not proven effective. Even for drugs which are approved as effective against such diseases, on average, such drugs will only be effective on about thirty percent of patients to which the drug is administered. Indeed, over a prolonged time scale, even penicillin-resistant bacteria have begun to emerge.
One way to explain this limited efficacy is that complex diseases may have alternate pathways along which they survive and regenerate. Those diseases which get locked into a single pathway of survival by single nucleotide polymorphism (SNP) profile can be effectively treated by a single drug that blocks the single pathway. However, some diseases, like cancer and HIV, for example, are flexible enough, so that if their primary path, as determined by the host SNP profile, is blocked using a single drug, after some time, the disease is able to change its survival path from the primary pathway to an alternate survival pathway. A multi-drug approach to these types of diseases is needed in order to block multiple survival pathways.
Although there have been some instances of multi-drug treatments of disease, such instances have been limited and disorganized, in a hindsight fashion, where there is a history of some effectiveness of two or more drugs, when each is used individually to treat a disease. The approach has then been to try the drugs together to see if an improved result can be achieved. One such example of this is the treatment of HIV by a “cocktail” approach. Another example of a multi-treatment approach, which has also been implemented only through a hindsight trial approach after experiencing some success with each treatment individually, is treatment of certain types of cancer with both radiation treatment and drug treatment. In addition to the hindsight track toward developing this regiment, it is noted that such treatments are also generally administered in sequentially, in a time-staggered fashion.
There is a need to develop organized, forward-looking ways of identifying treatment combinations for potential use together in the treatment of a disease. There is a need to treat diseases, such as viral diseases, in a complex way, because the organisms causing the diseases are very complex, able to mutate and/or use other mechanisms to survive along a different pathway when one pathway is cut off by a single treatment. Likewise, cancers, and some of the other more complex diseases that have been studied for a long time, with no cure found to date, may find more successful treatment regimens when treated multidimensionally. One-dimensional approaches (i.e., as addressed by a single type of treatment) to treatment of many of the more complex diseases have been unsuccessful to date, but generally the big pharmaceutical companies currently continue in their quests to find a “silver bullet”, i.e., a single drug, to cure a disease.
What is needed are forward looking screening and discovery techniques for identifying treatments that may be used in combination for treatment of disease. Hence, treatments in combination can create the requisite complexity to challenge sophisticated diseases. There needs to be a strategy, for using foresight in developing multi-treatment approaches, and to move away from the paradigm of drug treatment, radiation treatment or other types of treatments in one-dimensional space, by thinking in multi-dimensional space, to provide treatments that act multi-dimensionally.
As noted, multiple treatments that are currently used are results of hindsight combinations. For example, it was known that the treatment of liver disease with interferon was shown to be effective, and that ribovirin could also show good results. By combining these treatments, after knowledge of their individual results, it was found that using ribovirin with interferon was more effective. Typically, drug interactions have been approached as a need to identify them to avoid them. What is needed is to look at drugs, as well as other possible types of treatment, to identify them as an advantage against disease, i.e., to identify positive interactions among multiple treatments.